Computational Design of Microstructure

During the last couple of decades, treatment of microstructure in materials science has been shifted from the diagnostic to design paradigm. Design of microstructure is inherently complex problems due to non linear spatial and temporal interaction of composition and parameters leading to the target properties. In most of the cases, different properties are reciprocally correlated i.e., improvement of one lead to the degradation of other. Also, the design of microstructure is a multiscale problem, as the knowledge of phenomena at range of scales from electronic to mesoscale is required for precise composition-microstructure-property determination. In the view of above, present chapter provides the introduction to computationally driven microstructure engineering in the framework of constitutive length scale in microstructure design. The important issues pertaining to design such as phase stability and interfaces has been explained. Additionally, the bird-eye view of various computational techniques in order of length scale has been introduced, with an aim to present the picture of combination of various techniques for solving microstructural design problems under various scenarios.

Modelling and Simulation in Engineering

2004

An algorithm for partially relaxing multiwell energy densities, such as for materials undergoing martensitic phase transitions, is presented here. The detection of the rank-one convex hull, which describes effective properties of such materials, is carried out for the most prominent nontrivial case, namely the so-called Tk-configurations. Despite the fact that the computation of relaxed energies (and with it effective properties) is inherently unstable, we show that the detection of these hulls (T4-configurations) can be carried out exactly and with high efficiency. This allows in practice for their computation to arbitrary precision. In particular, our approach to detect these hulls is not based on any approximation or grid-like discretization. This makes the approach very different from previous (unstable and computationally expensive) algorithms for the computation of rank-one convex hulls or sequential-lamination algorithms for the simulation of martensitic microstructure. It ca...

Materials Research, 1999

Structure is at the heart of the materials science paradigm connecting processing with properties. In the hierarchy of structures that exist in materials microstructure offers the richest variety of structural arrangements. This variety is often conveniently accessible, e.g., simply by heat treatment or mechanical deformation. Exploration of the relation between properties and microstructure serves to establish a target range of microstructural states that will perform. In order to attain a target microstructure it is necessary to understand what microstructures are, and how they evolve in processing. This presentation focuses upon the set of tools that must be combined to achieve this control: 1. Geometry 2 Thermodynamics 3. Kinematics 4. Kinetics. The content of these tools is reviewed briefly and their uses illustrated in developing an understanding of how microstructures evolve. In this development an attempt is made to carry the description of each microstructural process as far as possible without making simplifying assumptions. The study of microstructures with this rigorous point of view was termed by F.N. Rhines, "microstructology".

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016), 2016

IOP Conference Series: Materials Science and Engineering

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Handbook of Micromechanics and Nanomechanics, 2013

This chapter outlines a novel continuum-based framework for modeling size effect ("smaller is stronger") in micro and nanostructured materials and structural systems. This framework is based on higher-order nonlocal gradient-dependent plasticity theory. Special emphasis is placed on incorporating the effects of interfaces and surfaces on the overall mechanical behavior of micro and nanostructured materials and systems.

Computational Materials Science, 2013

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.

International Journal of Solids and Structures, 2005

Proper quantitative characterization of microstructures, for the purpose of modeling the effective properties, is discussed. This is a broad subject that covers different physical properties (elastic, conductive, transport, etc.), as well as various types of microstructures. The present work focuses on microstructures that can be characterized as continuous matrices containing isolated inhomogeneities of diverse shapes, properties and orientations. We address their proper quantitative characterization in the context of elastic and conductive properties (transport and fracture-related properties are also briefly discussed). Proper microstructural parameters must correctly represent the individual inhomogeneity contributions to the considered property. They may differ for different physical properties. The key problem is to identify the mentioned individual contributions. For the elastic properties, we demonstrate, on a number of microstructures, how the proper parameters are implied by the elastic potential. Relative importance of various ''irregularity factors'' (shape irregularities, orientation scatter) is analyzed. We discuss similarities and differences between microstructural parameters intended for different physical properties. The possibility of explicit cross-property connections between two physical properties depends on whether the proper microstructural parameters for these two properties are sufficiently similar. We outline such explicit connections between the elastic and the conductive properties. The micromechanical approach is compared with the one based on an a priori introduced ''fabric'' tensors and general tensor representations that contain a number of uncertain factors. Various problems arising in this context are discussed.

The mechanical properties of materials are inherently multiscale, depending on phenomena at all length scales. Hence, multiscale modeling is a huge scientific challenge as well as a critical necessity for successful manipulation of material properties. This proposed research aims to investigate the microstructure (i.e., grain and inclusion) effect on the material properties especially for the system which involve two characteristic microstructure features at distinct length scales using hierarchical multiscale method. The fundamental understanding of multiscale behavior is the key to the utilization of nano-materials and to the design of material systems contained nano-materials. In polycrystalline nanofilm, two distinct characteristic sizes, i.e. grain size of micrometers and film thickness of nanometers, are involved. The typical size of inclusion would vary significantly due to manufacturing process. The hierarchical multiscale simulation method, which integrates atomistic and co...